Title :
Global stability analysis of neural networks with multiple time varying delays
Author :
Ensari, Tolga ; Arik, Sabri
Author_Institution :
Dept. of Comput. Eng., Istanbul Univ., Turkey
Abstract :
In this note, we study the equilibrium and stability properties of neural networks with time varying delays. Our main results give sufficient conditions for the existence, uniqueness and global asymptotic stability of the equilibrium point. The proposed conditions establish the relationships between network parameters of the neural systems and the delay parameters. The obtained results are applicable to all continuous nonmonotonic neuron activation functions and do not require the interconnection matrices to be symmetric. Some examples are also presented to compare our results with the previous results derived in the literature.
Keywords :
asymptotic stability; delays; neural nets; time-varying systems; continuous nonmonotonic neuron activation function; global asymptotic stability; global stability analysis; multiple time varying delays; neural network; Asymptotic stability; Convergence; Delay effects; Delay systems; Neural networks; Neurons; Stability analysis; Steady-state; Sufficient conditions; Symmetric matrices; Delayed neural networks; Lyapunov functionals; equilibrium and stability analysis;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2005.858634